It’s off topic, I know, but does anyone here have any really good articles or papers indicating why correct AI timelines would be short? This seems like a good place to ask and I’m not aware of a better one, which is why I’m asking here even though I know I’m not supposed to.
Personally I think the Most Important Century series is closest to my own thinking, though there isn’t any single source that would completely account for my views. Then again I think my timelines are longer than some of the other people in the comments, and I’m not aware of a good comprehensive write up of the case for much shorter timelines.
I’d like to see more posts like these (including counterarguments or reviews (example 1, example 2)), since timelines are highly relevant to career plans.
It’s off topic, I know, but does anyone here have any really good articles or papers indicating why correct AI timelines would be short? This seems like a good place to ask and I’m not aware of a better one, which is why I’m asking here even though I know I’m not supposed to.
Personally I think the Most Important Century series is closest to my own thinking, though there isn’t any single source that would completely account for my views. Then again I think my timelines are longer than some of the other people in the comments, and I’m not aware of a good comprehensive write up of the case for much shorter timelines.
These posts provide some interesting points:
Two-year update on my personal AI timelines
Fun with +12 OOMs of Compute
AI Timelines via Cumulative Optimization Power: Less Long, More Short
Why I think strong general AI is coming soon
What a compute-centric framework says about AI takeoff speeds—draft report
Disagreement with bio anchors that lead to shorter timelines
“AGI Timelines” section of PAIS #2
I’d like to see more posts like these (including counterarguments or reviews (example 1, example 2)), since timelines are highly relevant to career plans.
I have a hypothesis that some people are updating towards shorter timelines because they didn’t pay much attention to AI capabilities until seeing some of 2022′s impressive (public) results. Indeed, 2022 included results like LaMDA, InstructGPT, chain-of-thought prompting, GopherCite, Socratic Models, PaLM, PaLM-SayCan, DALL-E 2, Flamingo, Gato, AI-assisted circuit design, solving International Math Olympiad problems, Copilot finishing its preview period, Parti, VPT, Minerva, DeepNash, Midjourney entering open beta, AlphaFold Protein Structure Database expanding from nearly 1 million to over 200 million structures, Stable Diffusion, AudioLM, ACT-1, Whisper, Make-A-Video, Imagen Video, AlphaTensor, CICERO, ChatGPT, RT-1, answering medical questions, and more.